Delirium in Elderly Patients and the Risk of Postdischarge Mortality, Institutionalization, and Dementia
01 Jan 2010-
TL;DR: Eurelings et al. as discussed by the authors found that older patients with delirium experienced increased long-term mortality in one study, but not in another, which may affect conclusions.
Abstract: DELIRIUM IS A SYNDROME OF acutely altered mental status characterized by inattent ion and a f luctuat ing course. With occurrence rates of up to half of older patients postoperatively, and even higher in elderly patients admitted to intensive care units, delirium is the most common complication in hospitalized older people. Delirium causes distress to patients and caregivers, has been associated with increased morbidity and mortality, and is a major burden to health care services in terms of expenditures. Numerous studies have addressed the long-term prognosis of older individuals who experienced delirium during hospitalization. The evidence that these studies provide is not entirely consistent (eg, older patients with delirium experienced increased long-term mortality in one study, but not in another). Elements of study design, such as delirium and outcome ascertainment and time to follow-up, may affect conclusions. Whether delirium independently contributes to poor outcome or merely represents a marker of underlying disease is especially relevant. The long-term detrimental seAuthor Affiliations: Department of Geriatric Medicine, Medical Center Alkmaar, Alkmaar, the Netherlands (Mr Witlox and Dr de Jonghe); Department of Neurology, Academic Medical Center, Amsterdam, the Netherlands(MsEurelingsandDrsEikelenboomandvanGool); Department of Geriatric Medicine, Kennemer Gasthuis, Haarlem,theNetherlands(DrKalisvaart);andGGZinGeest, Amsterdam, the Netherlands (Dr Eikelenboom). Corresponding Author: Willem A. van Gool, MD, PhD, Department of Neurology, Academic Medical Center, PO Box 22700, 1100 DE Amsterdam, the Netherlands (w.a.vangool@amc.uva.nl). Context Delirium is a common and serious complication in elderly patients. Evidence suggests that delirium is associated with long-term poor outcome but delirium often occurs in individuals with more severe underlying disease.
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TL;DR: In view of the complex multifactorial causes of delirium, multicomponent non-pharmacological risk factor approaches are the most effective strategy for prevention and no convincing evidence shows that pharmacological prevention or treatment is effective.
2,359 citations
TL;DR: The economic impact of delirium is substantial, rivaling the health care costs of falls and diabetes mellitus, and the need for increased efforts to mitigate this clinically significant and costly disorder is highlighted.
Abstract: BACKGROUND: While delirium has been increasingly recognized as a serious and potentially preventable condition, its long-term implications are not well understood. This study determined the total 1-year health care costs associated with delirium. METHODS: Hospitalized patients aged 70 years and older who participated in a previous controlled clinical trial of a delirium prevention intervention at an academic medical center between 1995 and 1998 were followed up for 1 year after discharge. Total inflation-adjusted health care costs, calculated as either reimbursed amounts or hospital charges converted to costs, were computed by means of data from Medicare administrative files, hospital billing records, and the Connecticut Long-term Care Registry. Regression models were used to determine costs associated with delirium after adjusting for patient sociodemographic and clinical characteristics. RESULTS: During the index hospitalization, 109 patients (13.0%) developed delirium while 732 did not. Patients with delirium had significantly higher unadjusted health care costs and survived fewer days. After adjusting for pertinent demographic and clinical characteristics, average costs per day survived among patients with delirium were more than 2(1/2) times the costs among patients without delirium. Total cost estimates attributable to delirium ranged from $16 303 to $64 421 per patient, implying that the national burden of delirium on the health care system ranges from $38 billion to $152 billion each year. CONCLUSIONS: The economic impact of delirium is substantial, rivaling the health care costs of falls and diabetes mellitus. These results highlight the need for increased efforts to mitigate this clinically significant and costly disorder. Language: en
834 citations
TL;DR: Nearly a third of patients admitted to an intensive care unit develop delirium, and these patients are at increased risk of dying during admission, longer stays in hospital, and cognitive impairment after discharge.
Abstract: Objectives To determine the relation between delirium in critically ill patients and their outcomes in the short term (in the intensive care unit and in hospital) and after discharge from hospital. Design Systematic review and meta-analysis of published studies. Data sources PubMed, Embase, CINAHL, Cochrane Library, and PsychINFO, with no language restrictions, up to 1 January 2015. Eligibility criteria for selection studies Reports were eligible for inclusion if they were prospective observational cohorts or clinical trials of adults in intensive care units who were assessed with a validated delirium screening or rating system, and if the association was measured between delirium and at least one of four clinical endpoints (death during admission, length of stay, duration of mechanical ventilation, and any outcome after hospital discharge). Studies were excluded if they primarily enrolled patients with a neurological disorder or patients admitted to intensive care after cardiac surgery or organ/tissue transplantation, or centered on sedation management or alcohol or substance withdrawal. Data were extracted on characteristics of studies, populations sampled, identification of delirium, and outcomes. Random effects models and meta-regression analyses were used to pool data from individual studies. Results Delirium was identified in 5280 of 16 595 (31.8%) critically ill patients reported in 42 studies. When compared with control patients without delirium, patients with delirium had significantly higher mortality during admission (risk ratio 2.19, 94% confidence interval 1.78 to 2.70; P Conclusions Nearly a third of patients admitted to an intensive care unit develop delirium, and these patients are at increased risk of dying during admission, longer stays in hospital, and cognitive impairment after discharge.
664 citations
TL;DR: This guideline is aimed to promote knowledge and education in the preoperative, intraoperative and postoperative setting not only among anaesthesiologists but also among all other healthcare professionals involved in the care of surgical patients.
Abstract: The purpose of this guideline is to present evidence-based and consensus-based recommendations for the prevention and treatment of postoperative delirium. The cornerstones of the guideline are the preoperative identification and handling of patients at risk, adequate intraoperative care, postoperative detection of delirium and management of delirious patients. The scope of this guideline is not to cover ICU delirium. Considering that many medical disciplines are involved in the treatment of surgical patients, a team-based approach should be implemented into daily practice. This guideline is aimed to promote knowledge and education in the preoperative, intraoperative and postoperative setting not only among anaesthesiologists but also among all other healthcare professionals involved in the care of surgical patients.
654 citations
TL;DR: It is now apparent in multiple chronic disease states, and in ageing, that microglia are primed by prior pathology, or by genetic predisposition, to respond more vigorously to subsequent inflammatory stimulation, thus transforming an adaptive CNS inflammatory response to systemic inflammation, into one that has deleterious consequences for the individual.
Abstract: It is well accepted that CNS inflammation has a role in the progression of chronic neurodegenerative disease, although the mechanisms through which this occurs are still unclear. The inflammatory response during most chronic neurodegenerative disease is dominated by the microglia and mechanisms by which these cells contribute to neuronal damage and degeneration are the subject of intense study. More recently it has emerged that systemic inflammation has a significant role to play in the progression of these diseases. Well-described adaptive pathways exist to transduce systemic inflammatory signals to the brain, but activation of these pathways appears to be deleterious to the brain if the acute insult is sufficiently robust, as in severe sepsis, or sufficiently prolonged, as in repeated stimulation with robust doses of inflammogens such as lipopolysaccharide (LPS). Significantly, moderate doses of inflammogens produce new pathology in the brain and exacerbate or accelerate features of disease when superimposed upon existing pathology or in the context of genetic predisposition. It is now apparent in multiple chronic disease states, and in ageing, that microglia are primed by prior pathology, or by genetic predisposition, to respond more vigorously to subsequent inflammatory stimulation, thus transforming an adaptive CNS inflammatory response to systemic inflammation, into one that has deleterious consequences for the individual. In this review, the preclinical and clinical evidence supporting a significant role for systemic inflammation in chronic neurodegenerative diseases will be discussed. Mechanisms by which microglia might effect neuronal damage and dysfunction, as a consequence of systemic stimulation, will be highlighted.
622 citations
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TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?
Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis.
Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4
Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted?
A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …
45,105 citations
TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.
Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure
37,989 citations
TL;DR: A checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion should improve the usefulness ofMeta-an analyses for authors, reviewers, editors, readers, and decision makers.
Abstract: ObjectiveBecause of the pressure for timely, informed decisions in public health
and clinical practice and the explosion of information in the scientific literature,
research results must be synthesized. Meta-analyses are increasingly used
to address this problem, and they often evaluate observational studies. A
workshop was held in Atlanta, Ga, in April 1997, to examine the reporting
of meta-analyses of observational studies and to make recommendations to aid
authors, reviewers, editors, and readers.ParticipantsTwenty-seven participants were selected by a steering committee, based
on expertise in clinical practice, trials, statistics, epidemiology, social
sciences, and biomedical editing. Deliberations of the workshop were open
to other interested scientists. Funding for this activity was provided by
the Centers for Disease Control and Prevention.EvidenceWe conducted a systematic review of the published literature on the
conduct and reporting of meta-analyses in observational studies using MEDLINE,
Educational Research Information Center (ERIC), PsycLIT, and the Current Index
to Statistics. We also examined reference lists of the 32 studies retrieved
and contacted experts in the field. Participants were assigned to small-group
discussions on the subjects of bias, searching and abstracting, heterogeneity,
study categorization, and statistical methods.Consensus ProcessFrom the material presented at the workshop, the authors developed a
checklist summarizing recommendations for reporting meta-analyses of observational
studies. The checklist and supporting evidence were circulated to all conference
attendees and additional experts. All suggestions for revisions were addressed.ConclusionsThe proposed checklist contains specifications for reporting of meta-analyses
of observational studies in epidemiology, including background, search strategy,
methods, results, discussion, and conclusion. Use of the checklist should
improve the usefulness of meta-analyses for authors, reviewers, editors, readers,
and decision makers. An evaluation plan is suggested and research areas are
explored.
17,663 citations
TL;DR: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative developed recommendations on what should be included in an accurate and complete report of an observational study, resulting in a checklist of 22 items (the STROBE statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles.
Abstract: Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the Web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
15,454 citations
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